SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1325 of 3304 papers

TitleStatusHype
Laplacian-based Cluster-Contractive t-SNE for High Dimensional Data Visualization—0
FastSVD-ML-ROM: A Reduced-Order Modeling Framework based on Machine Learning for Real-Time Applications—0
SSBNet: Improving Visual Recognition Efficiency by Adaptive Sampling—0
Principal Geodesic Analysis of Merge Trees (and Persistence Diagrams)—0
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
Deep Sufficient Representation Learning via Mutual Information—0
CausNet : Generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraintsCode0
Natural language processing for clusterization of genes according to their functions—0
Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation—0
Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions—0
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction—0
On the Selection of Tuning Parameters for Patch-Stitching Embedding Methods—0
Beam-Space MIMO Radar for Joint Communication and Sensing with OTFS Modulation—0
Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution RegressionCode0
Horizontal and Vertical Attention in Transformers—0
Stacked Autoencoder Based Multi-Omics Data Integration for Cancer Survival PredictionCode0
UDRN: Unified Dimensional Reduction Neural Network for Feature Selection and Feature Projection—0
Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data—0
A Hybrid Approach for Binary Classification of Imbalanced Data—0
Tricking the Hashing Trick: A Tight Lower Bound on the Robustness of CountSketch to Adaptive Inputs—0
UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes—0
Local manifold learning and its link to domain-based physics knowledgeCode0
Extreme compression of sentence-transformer ranker models: faster inference, longer battery life, and less storage on edge devices—0
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns—0
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified